Host-microbial interactions in the metabolism of different dietary fats

Chadaideh, Katia S.; Carmody, Rachel N.

doi:10.1016/j.cmet.2021.04.011

Cited by 36 publications

(40 citation statements)

References 204 publications

(258 reference statements)

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“…In this sense, our results on miRNAs could reflect the gut microbiota shifts in response to dietary fat recently reviewed by Chadaideh and Carmody. 76 In the present study, among the three investigated groups, the analysis of the dietary information recorded in the EPIC questionnaires confirmed the expected differences in weekly food consumption and estimated daily nutrient intake. Nutrients and specific diet components have been implicated in the modulation of miRNA expression in in vitro/in vivo models and, as a consequence, in all miRNA-mediated molecular mechanisms.…”

Section: Discussionsupporting

confidence: 84%

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Stool microRNA profiles reflect different dietary and gut microbiome patterns in healthy individuals

Tarallo

Ferrero

Filippis

et al. 2021

Gut

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ObjectivesMicroRNA (miRNA) profiles have been evaluated in several biospecimens in relation to common diseases for which diet may have a considerable impact. We aimed at characterising how specific diets are associated with the miRNome in stool of vegans, vegetarians and omnivores and how this is reflected in the gut microbial composition, as this is still poorly explored.DesignWe performed small RNA and shotgun metagenomic sequencing in faecal samples and dietary recording from 120 healthy volunteers, equally distributed for the different diets and matched for sex and age.ResultsWe found 49 miRNAs differentially expressed among vegans, vegetarians and omnivores (adj. p <0.05) and confirmed trends of expression levels of such miRNAs in vegans and vegetarians compared with an independent cohort of 45 omnivores. Two miRNAs related to lipid metabolism, miR-636 and miR-4739, were inversely correlated to the non-omnivorous diet duration, independently of subject age. Seventeen miRNAs correlated (|rho|>0.22, adj. p <0.05) with the estimated intake of nutrients, particularly animal proteins, phosphorus and, interestingly, lipids. In omnivores, higher Prevotella and Roseburia and lower Bacteroides abundances than in vegans and vegetarians were observed. Lipid metabolism-related miR-425-3p and miR-638 expression levels were associated with increased abundances of microbial species, such as Roseburia sp. CAG 182 and Akkermansia muciniphila, specific of different diets. An integrated analysis identified 25 miRNAs, 25 taxa and 7 dietary nutrients that clearly discriminated (area under the receiver operating characteristic curve=0.89) the three diets.ConclusionStool miRNA profiles are associated with specific diets and support the role of lipids as a driver of epigenetic changes and host-microbial molecular interactions in the gut.

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Section: Discussionsupporting

confidence: 84%

“…In this sense, our results on miRNAs could reflect the gut microbiota shifts in response to dietary fat recently reviewed by Chadaideh and Carmody. 76 …”

Section: Discussionmentioning

confidence: 99%

Stool microRNA profiles reflect different dietary and gut microbiome patterns in healthy individuals

Tarallo

Ferrero

Filippis

et al. 2021

Gut

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“…The gut microbiota participates in host metabolism by interacting with host signaling pathways ( 16 ). Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of changed microbiota genes indicated that eight major signaling pathways were upset by HFD and recovered by A10-FMT and/or Con-FMT in the colon, cecum, and/or small intestine ( Fig.…”

Section: Resultsmentioning

confidence: 99%

“…2J ). It is known that HFD upsets lipid metabolism because the host and gut microbiota interact together to support this process ( 16 ). Furthermore, it has been reported that the gut microbiota Mucispirillum is involved in lipid metabolism ( 2 , 12 ), and it was increased by HFD while decreased by A10-FMT.…”

Section: Resultsmentioning

confidence: 99%

Gut Microbiota-Testis Axis: FMT Mitigates High-Fat Diet-Diminished Male Fertility via Improving Systemic and Testicular Metabolome

et al. 2022

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“…In animal models, changes to the gut microbiome can substantially alter weight gain and obesity, without changes in total energy intake or physical activity ( 16 , 17 ); and changes in both absolute and relative microbiome energy use influence host weight gain ( 10 , 11 ). Such complexity also extends to different dietary fats, whose effective caloric value, for the host, may vary depending on the type of food consumed and host–microbial interactions ( 18 ). In sum, a differential partitioning of consumed energy, due to population changes in foods consumed and microbial characteristics, could be a contributor to the obesity epidemic.…”

Section: The Obesity Epidemic: Changing Biology?mentioning

confidence: 99%

Perspective: Obesity—an unexplained epidemic

Mozaffarian

2022

The American Journal of Clinical Nutrition

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Since 1980, obesity prevalence among US adults has soared from 14% to 42%. The commonly accepted explanation is pervasive overeating: ever-increasing energy intake as the population gains weight, year after year. However, evidence does not support this hypothesis. National data on energy intake and energy availability show increases between 1961 and 2000, during modern industrialization of food; but a plateau or declines thereafter—even as obesity continued rising—and while physical activity modestly increased. Thus, Americans appear to be eating relatively less since 2000, for ever-increasing body sizes, as time has progressed. Although both energy intake and energy availability are measured with error, such errors would have to be new since 2000 and systematically increasing over time for these 2 separate, independent measures. Given the tremendous societal consequences of obesity, and failure to date of energy balance–focused interventions to stem the tide, it is critical for the scientific community to consider and test alternative hypotheses. Growing evidence suggests complex, interrelated biological interactions between food processing (including acellular nutrients, depleted prebiotics, additives), gut microbial composition and function, host metabolic expenditure, and intergenerational transmission of risk (including epigenetics, noncoding RNAs, microbial species). In this paradigm, whereas increasing energy intake may have contributed to rising obesity in earlier years, today pervasive adiposity and its physiologic adaptations have created a biological milieu which interacts with industrialized foods to promote escalating obesity, even with stable energy intake—a self-sustaining, difficult-to-reverse cycle. These scientific hypotheses must be rigorously evaluated, because even partial confirmation would dramatically shift and expand current prevention and treatment strategies. Urgent new investment in research is required. Simultaneously, uncertain evidence on the obesity epidemic's primary drivers does not mean there is no evidence on actions that can help, and existing science must be more rapidly translated and refined into clinical, public health, and policy interventions.

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Host-microbial interactions in the metabolism of different dietary fats

Cited by 36 publications

References 204 publications

Stool microRNA profiles reflect different dietary and gut microbiome patterns in healthy individuals

Stool microRNA profiles reflect different dietary and gut microbiome patterns in healthy individuals

Gut Microbiota-Testis Axis: FMT Mitigates High-Fat Diet-Diminished Male Fertility via Improving Systemic and Testicular Metabolome

Perspective: Obesity—an unexplained epidemic

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